Prelert Anomaly Detective API Engine Beta

Get fast, accurate anomaly detection across any data source with Prelert’s behavioral analytics platform

Behavioral analytics for IT security and operations teams

Prelert’s behavioral analytics platform analyzes log data from a variety of data stores, finds anomalies that can indicate advanced cyber threats and IT performance problems. Using machine learning anomaly detection, Prelert offers:


img-real-problems-01Early Detection of Incidents

Detect advanced threat activity such as data exfiltration and command and control communication in near real-time. Identify IT operations problems before users report them.

img-real-problems-02Faster Root Cause Discovery

Find the root cause of anomalies faster. Get the full story behind cyberthreats and IT ops issues with algorithms that learn minute-to-minute what is normal for your environment.  Involve fewer people in triage and get answers fast.

img-real-problems-03Reduced False Positives

Because Prelert’s analytics run on log data from a broad set of sources, they are able to consider more context than monitoring tools that rely on a single source.  This additional context helps to significantly reduce false positives.

Anomaly Detective API Engine Beta:
Put Machine Learning to Work

The Prelert API engine helps you automate the analysis of massive data sets across a wide range of data sources, eliminating manual effort and human error. Downloaded as a software application with a REST API, Prelert analyzes your data and provides anomaly results via the REST API.


  • 100% unsupervised machine learning
  • Cuts through millions of data points in seconds
  • Identifies anomalous behavior patterns in near real-time
  • Ranks anomalies by probability of occurrence
  • Gives you the actionable insights you need to act quickly
  • Open REST API and Open Source UI

Works with:

  • Log management and search platforms (e.g. Elastic Stack, Sumo Logic)
  • Big Data Stores (e.g. Hadoop)
  • Hosted Big Data Stores (e.g. Google Data Store, AWS Red Shift)

Sample Use Cases

Security Analytics

  • Detect DNS Data Exfiltration (Tunneling) in DNS Query Requests
  • Detect Suspicious Network Activity (App-Port) in Firewall Logs
  • Detect Suspicious Login Activity in Endpoint Detection and Response Logs
      View more

IT Operations Insights

  • Analyze Operational Metrics
  • Discover Root Cause
  • Track Business KPIs

Retail Order Analytics

  • Detect Revenue-Impacting Events
  • Accurately Model Periodic Behaviors
  • Find Operational, Process-Related, or Externally-Created Issues

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